Mark the Markdown processor a util, and allow it to take inputs

src/pipecat/services/ai_services.py

@@ -37,6 +37,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transcriptions.language import Language
 from pipecat.utils.audio import calculate_audio_volume
 from pipecat.utils.string import match_endofsentence
+from pipecat.utils.text.base_text_filter import BaseTextFilter
 from pipecat.utils.time import seconds_to_nanoseconds
 from pipecat.utils.utils import exp_smoothing
 
@@ -172,6 +173,7 @@ class TTSService(AIService):
         stop_frame_timeout_s: float = 1.0,
         # TTS output sample rate
         sample_rate: int = 16000,
+        text_filter: Optional[BaseTextFilter] = None,
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -182,6 +184,7 @@ class TTSService(AIService):
         self._sample_rate: int = sample_rate
         self._voice_id: str = ""
         self._settings: Dict[str, Any] = {}
+        self._text_filter: Optional[BaseTextFilter] = text_filter
 
         self._stop_frame_task: Optional[asyncio.Task] = None
         self._stop_frame_queue: asyncio.Queue = asyncio.Queue()
@@ -242,6 +245,8 @@ class TTSService(AIService):
                 self.set_model_name(value)
             elif key == "voice":
                 self.set_voice(value)
+            elif key == "text_filter" and self._text_filter:
+                self._text_filter.update_settings(value)
             else:
                 logger.warning(f"Unknown setting for TTS service: {key}")
 
@@ -312,6 +317,8 @@ class TTSService(AIService):
             return
 
         await self.start_processing_metrics()
+        if self._text_filter:
+            text = self._text_filter.filter(text)
         await self.process_generator(self.run_tts(text))
         await self.stop_processing_metrics()
         if self._push_text_frames: